Improving large scale flood forecasting and preparation

By Matt Ables

It has been a year since significant and steady rains raised Lake Ontario’s water levels and local authorities are working to avoid future flooding and battering of the shoreline. Winter water levels alone have not been providing an accurate indicator of peak levels seen later in the spring. By monitoring weather and hydrologic conditions, municipalities and regions can better respond to extreme weather events and improve climate resilience.

Ontario is among the provinces best prepared to respond to flood risks and mitigate damages. Several conservation authorities, like Lake Simcoe Regional and Grand River, have independently dedicated resources necessary to conduct research and apply knowledge from their findings to policy and action.

With a similar vision and goals for more science-based decisions, a majority of conservation authorities have formed data sharing hubs. Establishing a single clearinghouse of validated data empowers each member of the cooperative group to easily, safely and seamlessly share information. This grassroots movement enables each organization to more accurately anticipate increases in hydrological levels. Moreover, each authority can better prepare for a weather event, before a gauge in its own monitoring network has detected any change.

Although data collection density has greatly increased, KISTERS web interoperability services utilize open data standards to make application programming interface (API) options available via hypertext transfer protocol (HTTP) for fast and efficient distribution of information. Authorized groups and individual users can also retrieve and calculate data.

Weather events can impact communities differently within the same region. So each member of the hub has the ability to apply different flood forecasting models like HEC-RAS, re-analyze past flooding events and prevent future flooding events with green infrastructure. Each authority also has new opportunities to enhance its public communications.

For example, the flood status near Belleville, Ontario, where the Quinte Conservation Authority is headquartered, may differ from outlook statements in Trenton and Mississauga, which are monitored by Lower Trent or Credit Valley conservation authorities, respectively. Forecasts for heavy rain, snowmelt or high wind, or a change in conditions on local waterways are factors. Each authority continually monitors and assesses conditions, and then posts flood status and low water status with dashboard-like widgets on their websites.

A broader approach

The same innovative technologies for data synthesis, validation, processing and interoperability are being applied continental wide. The Office of Water Prediction of the National Oceanic and Atmospheric Administration has implemented the National Water Model (NWM). Developed by Dr. David Maidment, this simulation model of observed and forecasted streamflow features complex representations of physical processes such as snowmelt, infiltration and movement of water through soil layers and terrain.

It runs hourly uncoupled analysis or simulation of current conditions. Short-range forecasts are executed hourly, while medium-range forecasts out to 10 days are produced four times per day. A daily ensemble long-range forecast to 30 days is also produced. All model configurations will provide streamflow for 2.7 million river reaches and other hydrologic information on 1 km and 250 m grids.

A project using NWM forecasts approximates flood impacts at stream and street level. As forecasts are ingested by KISTERS’ big data technology stack, precipitation and flow information are converted into water level data, utilizing rating curves computed using the height above nearest drainage (HAND) method, also developed by Dr. Maidment. Flow, precipitation, water level, and evaluations of forecast data versus actual gauge measurements are then provided to Esri for geoprocessing and the creation of inundation maps. The system also ingests official forecasts.

The partnership ensures the best combination of data-processing workflows, capabilities and spatial analysis is applied to address big water issues.

As a result, emergency management professionals can easily view approximate flood levels and address inundation, using 18-hour or 10-day forecasts. The NWM viewer or visualization tool serves as a dashboard. The display streamlines a significant volume of information critical to first responders and their technical advisors, including hydrographs of forecasted flow or discharge rate, computed stage or water level, and surface precipitation rate. The system performs ongoing evaluations of forecast data versus actual gauge measurements. Sentinel sites, or river basins with high probability of being severely impacted by extreme weather events, are closely monitored.

Open data standards like WaterML 2.0 and SOS to transfer data, and KISTERS web interoperability services enable the innovative flood forecasting system to connect data streams that were previously isolated.

The additional volume and integrity of data quickly delivers insight into small creeks and rivers previously unmonitored or unreliably monitored. The need for high accuracy, real-time information on flow and stage has also brought about the deployment of cutting-edge monitoring devices.

Modern radar sensors that measure water levels and velocity can be used to produce discharge records at stations where complex flow conditions make the application of conventional stage-discharge measurement methods ineffective or impossible. Conditions include flow reversals, backwater effects, and hysteresis effects, and they can occur when the onset of flooding has been reached. Simple output from these Doppler frequency devices supports integration into most any data measurement system.

Future approaches

The factors that affected planning decisions and construction of existing flood protection structures are changing. Old systems for managing weather events are failing to keep pace with the volume, velocity and variability of flood forecasting data being collected. Uncertainty is still sure to exist. Costs to update or construct flood protection barriers are sure to rise. Loss of experience-based knowledge also increases with retirement.

However, the ability to adopt modern and scalable technologies to help make sense of all that data to address flooding risks is readily available. Effective tools for data collection, management and analysis help inform long-term decisions related to extreme weather events.

Considering the magnitude of change and the level of resilience cities desire, no municipality will be able to monitor, plan and respond alone. Private-public partnerships, inter-government agency data sharing hubs, and public collaboration will be essential.

Matt Ables is with KISTERS North America. This article appears in ES&E Magazine’s June 2018 issue.